GenAI_Roadmap.md

Gen AI Roadmap for Everyone - 2024

     

Your 85%+ go to toolkit for Enterprise Grade GenAI..Tech especially AI evolves fast, but the fundamentals are forever.

⭐ Star this repo to stay updated with the latest GenAI Use cases, many more Enterprise grade Use cases (Especially AI Agents) are in the pipeline and will be updated here soon. Stay tuned :)

🔧 Set up related GenAI use cases (you can do this step later, when you're ready to code)

• - How to setup Google Colab Notebook for free GPU
• - How to setup Google's free Gemini Pro API Key
• GenAI Use cases

📚 Fundamentals of GenAI (1.2 Hr)

• - Generative AI in Nutshell
• - LLM Explained (By 3blue1brown)
• - Intro to GenAI
• - What is LLM

Optional References

• - What is LLM
• Useful LLM Concepts

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  • Cohere Blog

  • Generative AI Guide

  • - Deep Learning Playlist (Famous 3blue1brown. Must go through if looking for broad AI Engineer role.)

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🤖 What is GPT? (28 Min)

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⚡What is Transformer? (10 Min)

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🗣️ Natural Language Processing (NLP) for beginners

• Tutorial Link
• Simple and Quick Understanding of NLP Basics Tutorial

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📜 Python

• - Python Core Crash Course (1 Hr)
• - Python DS Crash Course (49 Min)

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☁️ Understanding Google Colab (22 Min)

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🤗 Huggingface Open Source Models (34 Min)

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• Official Doc

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🏠 Running LLM Locally using Ollama (~ 1.5 Hr)

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Some Cool examples (18 Min)

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🔗 LangChain

I prefer going through the LangChain documentation, which is well-written and includes example notebooks, as it updates very quickly. Referring to most of the LangChain YouTube videos might give you outdated content after a few weeks.

• Official Doc

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🎯 Prompt Engineering

• Prompt Engineering Colab Notebook
• Course
  • Coursera Specialization

Optional References

• Blogs
  • Prompting Guide
  • Google's Five Best practices for Prompt Engineering
  • Google's doc of Prompt Engineering
  • OpenAI Best Practices
  • OpenAI Guide

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📊 What is Vector Database?

• Pinecone Blog

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🗺️ What is Vector Embedding?

• Embedding Model Notebook
• Qdrant Blog

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📖 RAG Tutorials (~2 Hr)

• Advance RAG Pdf

• - Complex Pdf Parsing

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Optional References

• Ragatouille-Book

• Graph RAG (New)

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⚖️ RAG Vs Prompt Engineering Vs Fine Tuning (15 Min)

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🔧 Fine Tuning LLM (~4 Hr)

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🤖 LLM Agents

• GenAI Agents - GitHub
• Deeplearning.ai Short Course - Agent
• Prompt Guide - LLM Agents

Optional References

• Deeplearning.ai Autogen
• Nvidia Blog
• Ttruefoundry Blog
• Agpt Blog
• Architecting & Testing reliable Agent (Using LangGraph)

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🔀 What is MultiModel? (7 Min)

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• Blog

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🧠 What is Mixture of Experts (MoE) (~30 Min)

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• Huggingface MoE Blog

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🎨 Streamlit for fast prototype UI

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• Official Doc

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🔍 LLM Evaluation

• Blogs
  • LLM Evaluation Ultimate Guide
  • Large Language Model Evaluation

Optional References

• LLM Evaluation
• Medium Blog

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🏭 LLMOPs & Productionization of GenAI applications

• Short Course - deeplearning.ai
• Specialization - Coursera

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🏆 LLM Leaderboard & Benchmarks

• Artificial Analysis AI
• LMSYS
• Huggingface open-llm-leaderboard

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📚 GenAI Use Cases (Used free Gemini Pro & huggingface LLMs only)

• - How to setup Google Colab Notebook for free GPU
• - How to setup Google's free Gemini Pro API Key
• - Conversational Analytics (Full Stack GenAI App using React, MongoDB, Free Gemini Pro LLM, Docker, Authentication & Authorisation using JWT oken)
• - Chat with Graph Database (Neo4j Graph Database, Gemini Pro LLM & Streamlit UI)
• - Build Personal AI Assistant with Claude-MCP
• - Complex Snapshot Based PDF Parsing with Docling, Markitdown, Llama-Vision, Claude, GPT-4 etc
• - Machine Translation (Gemini Pro LLM & Streamlit UI)
• - Tagging (Gemini Pro LLM & Streamlit UI)
• Webscraping (Gemini Pro LLM & Streamlit UI)
• - Chatbot with SQL Database (Huggingface Opensource LLM & Streamlit UI)
• - Chatbot with CSV (Huggingface Opensource LLM)
• - Text to SQL generation (Huggingface Opensource LLM)
• - Text Summarization (Huggingface Opensource LLM)
• - Fully local RAG Agent with Llama3.1 (By LangChain Team)

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📝 GenAI Interview Questions & Answers

• PDF

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🤝 Contributing

Contributions to add good impactful resources/codes to the list are welcome!

Here’s how you can help:

1. Fork the Repository

   Click on the "Fork" button at the top right corner of the page to create a personal copy of the repository.

2. Clone the Repository

   Clone your forked repository to your local machine:

   git clone https://github.com/genieincodebottle/generative-ai.git

3. Create a New Branch

   Create a new branch for your feature or bug fix:

   git checkout -b your-branch-name

4. Make Your Changes

   Make your changes and commit them with a clear message:

   git commit -m "Brief description of your changes"

5. Push Your Changes Push your changes to your forked repository:

   git push origin your-branch-name

6. Create a Pull Request

   Go to the original repository and create a pull request. Make sure to explain your changes and why they should be merged.